Contrastive Retrospection: honing in on critical steps for rapid learning and generalization in RL - Chen Sun; Wannan Yang; Thomas Jiralerspong; Dane Malenfant; Benjamin Alsbury-Nealy; Yoshua Bengio; Blake A. Richards (Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16, 2023, 2023)

DynGFN: Towards Bayesian Inference of Gene Regulatory Networks with GFlowNets - Lazar Atanackovic; Alexander Tong; Bo Wang; Leo J. Lee; Yoshua Bengio; Jason S. Hartford (Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16, 2023, 2023)

Improving *day-ahead* Solar Irradiance Time Series Forecasting by Leveraging Spatio-Temporal Context - Oussama Boussif; Ghait Boukachab; Dan Assouline; Stefano Massaroli; Tianle Yuan; Loubna Benabbou; Yoshua Bengio (Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16, 2023, 2023)

Joint Bayesian Inference of Graphical Structure and Parameters with a Single Generative Flow Network - Tristan Deleu; Mizu Nishikawa-Toomey; Jithendaraa Subramanian; Nikolay Malkin; Laurent Charlin; Yoshua Bengio (Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16, 2023, 2023)

GEO-Bench: Toward Foundation Models for Earth Monitoring - Alexandre Lacoste; Nils Lehmann; Pau Rodríguez; Evan D. Sherwin; Hannah Kerner; Björn Lütjens; Jeremy Irvin; David Dao; Hamed Alemohammad; Alexandre Drouin; Mehmet Gunturkun; Gabriel Huang; et al. (Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16, 2023, 2023)

Laughing Hyena Distillery: Extracting Compact Recurrences From Convolutions - Stefano Massaroli; Michael Poli; Daniel Y. Fu; Hermann Kumbong; Rom N. Parnichkun; David W. Romero; Aman Timalsina; Quinn McIntyre; Beidi Chen; Atri Rudra; Ce Zhang; Christopher Ré; et al. (Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16, 2023, 2023)

Reusable Slotwise Mechanisms - Bailey Trang Nguyen; Amin Mansouri; Kanika Madan; Khuong Nguyen; Kartik Ahuja; Dianbo Liu; Yoshua Bengio (Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16, 2023, 2023)

HyenaDNA: Long-Range Genomic Sequence Modeling at Single Nucleotide Resolution - Eric Nguyen; Michael Poli; Marjan Faizi; Armin W. Thomas; Michael Wornow; Callum Birch-Sykes; Stefano Massaroli; Aman Patel; Clayton M. Rabideau; Yoshua Bengio; Stefano Ermon; Christopher Ré; et al. (Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16, 2023, 2023)

SatBird: a Dataset for Bird Species Distribution Modeling using Remote Sensing and Citizen Science Data - Mélisande Teng; Amna Elmustafa; Benjamin Akera; Yoshua Bengio; Hager Radi Abdelwahed; Hugo Larochelle; David Rolnick (Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16, 2023, 2023)

Let the Flows Tell: Solving Graph Combinatorial Problems with GFlowNets - Dinghuai Zhang; Hanjun Dai; Nikolay Malkin; Aaron C. Courville; Yoshua Bengio; Ling Pan (Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16, 2023, 2023)

Stochastic Generative Flow Networks - Ling Pan; Dinghuai Zhang; Moksh Jain; Longbo Huang; Yoshua Bengio (Uncertainty in Artificial Intelligence, UAI 2023, July 31 - 4 August 2023, Pittsburgh, PA, USA, 2023)

MixupE: Understanding and improving Mixup from directional derivative perspective - Yingtian Zou; Vikas Verma; Sarthak Mittal; Wai Hoh Tang; Hieu Pham; Juho Kannala; Yoshua Bengio; Arno Solin; Kenji Kawaguchi (Uncertainty in Artificial Intelligence, UAI 2023, July 31 - 4 August 2023, Pittsburgh, PA, USA, 2023)

Regeneration Learning: A Learning Paradigm for Data Generation - Xu Tan; Tao Qin; Jiang Bian; Tie-Yan Liu; Yoshua Bengio (CoRR, 2023)

Leveraging the Third Dimension in Contrastive Learning - Sumukh K. Aithal; Anirudh Goyal; Alex Lamb; Yoshua Bengio; Michael Mozer (CoRR, 2023)

A theory of continuous generative flow networks - Salem Lahlou; Tristan Deleu; Pablo Lemos; Dinghuai Zhang; Alexandra Volokhova; Alex Hernández-García; Léna Néhale Ezzine; Yoshua Bengio; Nikolay Malkin (CoRR, 2023)

Conditional Flow Matching: Simulation-Free Dynamic Optimal Transport - Alexander Tong; Nikolay Malkin; Guillaume Huguet; Yanlei Zhang; Jarrid Rector-Brooks; Kilian Fatras; Guy Wolf; Yoshua Bengio (CoRR, 2023)

GFlowNets for AI-Driven Scientific Discovery - Moksh Jain; Tristan Deleu; Jason S. Hartford; Cheng-Hao Liu; Alex Hernández-García; Yoshua Bengio (CoRR, 2023)

Better Training of GFlowNets with Local Credit and Incomplete Trajectories - Ling Pan; Nikolay Malkin; Dinghuai Zhang; Yoshua Bengio (CoRR, 2023)

DynGFN: Bayesian Dynamic Causal Discovery using Generative Flow Networks - Lazar Atanackovic; Alexander Tong; Jason S. Hartford; Leo J. Lee; Bo Wang; Yoshua Bengio (CoRR, 2023)

Distributional GFlowNets with Quantile Flows - Dinghuai Zhang; Ling Pan; Ricky T. Q. Chen; Aaron C. Courville; Yoshua Bengio (CoRR, 2023)

Sources of Richness and Ineffability for Phenomenally Conscious States - Xu Ji; Eric Elmoznino; George Deane; Axel Constant; Guillaume Dumas; Guillaume Lajoie; Jonathan Simon; Yoshua Bengio (CoRR, 2023)

GFlowNet-EM for learning compositional latent variable models - Edward J. Hu; Nikolay Malkin; Moksh Jain; Katie Everett; Alexandros Graikos; Yoshua Bengio (CoRR, 2023)

Stochastic Generative Flow Networks - Ling Pan; Dinghuai Zhang; Moksh Jain; Longbo Huang; Yoshua Bengio (CoRR, 2023)

Reusable Slotwise Mechanisms - Bailey Trang Nguyen; Amin Mansouri; Kanika Madan; Khuong Nguyen; Kartik Ahuja; Dianbo Liu; Yoshua Bengio (CoRR, 2023)

Hyena Hierarchy: Towards Larger Convolutional Language Models - Michael Poli; Stefano Massaroli; Eric Nguyen; Daniel Y. Fu; Tri Dao; Stephen Baccus; Yoshua Bengio; Stefano Ermon; Christopher Ré (CoRR, 2023)

FAENet: Frame Averaging Equivariant GNN for Materials Modeling - Alexandre Duval; Victor Schmidt; Alex Hernández-García; Santiago Miret; Fragkiskos D. Malliaros; Yoshua Bengio; David Rolnick (CoRR, 2023)

Constant Memory Attentive Neural Processes - Leo Feng; Frederick Tung; Hossein Hajimirsadeghi; Yoshua Bengio; Mohamed Osama Ahmed (CoRR, 2023)

Model evaluation for extreme risks - Toby Shevlane; Sebastian Farquhar; Ben Garfinkel; Mary Phuong; Jess Whittlestone; Jade Leung; Daniel Kokotajlo; Nahema Marchal; Markus Anderljung; Noam Kolt; Lewis Ho; Divya Siddarth; et al. (CoRR, 2023)

Let the Flows Tell: Solving Graph Combinatorial Optimization Problems with GFlowNets - Dinghuai Zhang; Hanjun Dai; Nikolay Malkin; Aaron C. Courville; Yoshua Bengio; Ling Pan (CoRR, 2023)

Attention Schema in Neural Agents - Dianbo Liu; Samuele Bolotta; He Zhu; Yoshua Bengio; Guillaume Dumas (CoRR, 2023)

Joint Bayesian Inference of Graphical Structure and Parameters with a Single Generative Flow Network - Tristan Deleu; Mizu Nishikawa-Toomey; Jithendaraa Subramanian; Nikolay Malkin; Laurent Charlin; Yoshua Bengio (CoRR, 2023)

Spotlight Attention: Robust Object-Centric Learning With a Spatial Locality Prior - Ayush Chakravarthy; Bailey Trang Nguyen; Anirudh Goyal; Yoshua Bengio; Michael C. Mozer (CoRR, 2023)

What if We Enrich day-ahead Solar Irradiance Time Series Forecasting with Spatio-Temporal Context? - Oussama Boussif; Ghait Boukachab; Dan Assouline; Stefano Massaroli; Tianle Yuan; Loubna Benabbou; Yoshua Bengio (CoRR, 2023)

Cycle Consistency Driven Object Discovery - Aniket Didolkar; Anirudh Goyal; Yoshua Bengio (CoRR, 2023)

GEO-Bench: Toward Foundation Models for Earth Monitoring - Alexandre Lacoste; Nils Lehmann; Pau Rodríguez; Evan David Sherwin; Hannah Kerner; Björn Lütjens; Jeremy Andrew Irvin; David Dao; Hamed Alemohammad; Alexandre Drouin; Mehmet Gunturkun; Gabriel Huang; et al. (CoRR, 2023)

Multi-Fidelity Active Learning with GFlowNets - Alex Hernández-García; Nikita Saxena; Moksh Jain; Cheng-Hao Liu; Yoshua Bengio (CoRR, 2023)

Constant Memory Attention Block - Leo Feng; Frederick Tung; Hossein Hajimirsadeghi; Yoshua Bengio; Mohamed Osama Ahmed (CoRR, 2023)

BatchGFN: Generative Flow Networks for Batch Active Learning - Shreshth A. Malik; Salem Lahlou; Andrew Jesson; Moksh Jain; Nikolay Malkin; Tristan Deleu; Yoshua Bengio; Yarin Gal (CoRR, 2023)

HyenaDNA: Long-Range Genomic Sequence Modeling at Single Nucleotide Resolution - Eric Nguyen; Michael Poli; Marjan Faizi; Armin W. Thomas; Callum Birch-Sykes; Michael Wornow; Aman Patel; Clayton M. Rabideau; Stefano Massaroli; Yoshua Bengio; Stefano Ermon; Stephen A. Baccus; et al. (CoRR, 2023)

Thompson sampling for improved exploration in GFlowNets - Jarrid Rector-Brooks; Kanika Madan; Moksh Jain; Maksym Korablyov; Cheng-Hao Liu; Sarath Chandar; Nikolay Malkin; Yoshua Bengio (CoRR, 2023)

Generative Flow Networks: a Markov Chain Perspective - Tristan Deleu; Yoshua Bengio (CoRR, 2023)

Simulation-free Schrödinger bridges via score and flow matching - Alexander Tong; Nikolay Malkin; Kilian Fatras; Lazar Atanackovic; Yanlei Zhang; Guillaume Huguet; Guy Wolf; Yoshua Bengio (CoRR, 2023)

International Institutions for Advanced AI - Lewis Ho; Joslyn Barnhart; Robert Trager; Yoshua Bengio; Miles Brundage; Allison Carnegie; Rumman Chowdhury; Allan Dafoe; Gillian K. Hadfield; Margaret Levi; Duncan Snidal (CoRR, 2023)

Benchmarking Bayesian Causal Discovery Methods for Downstream Treatment Effect Estimation - Chris Chinenye Emezue; Alexandre Drouin; Tristan Deleu; Stefan Bauer; Yoshua Bengio (CoRR, 2023)

AI For Global Climate Cooperation 2023 Competition Proceedings - Yoshua Bengio; Prateek Gupta; Lu Li; Soham Phade; Sunil Srinivasa; Andrew Williams; Tianyu Zhang; Yang Zhang; Stephan Zheng (CoRR, 2023)

Consciousness in Artificial Intelligence: Insights from the Science of Consciousness - Patrick Butlin; Robert Long; Eric Elmoznino; Yoshua Bengio; Jonathan Birch; Axel Constant; George Deane; Stephen M. Fleming; Chris Frith; Xu Ji; Ryota Kanai; Colin Klein; et al. (CoRR, 2023)

Tree Cross Attention - Leo Feng; Frederick Tung; Hossein Hajimirsadeghi; Yoshua Bengio; Mohamed Osama Ahmed (CoRR, 2023)

Combining Spatial and Temporal Abstraction in Planning for Better Generalization - Mingde Zhao; Safa Alver; Harm van Seijen; Romain Laroche; Doina Precup; Yoshua Bengio (CoRR, 2023)

Discrete, compositional, and symbolic representations through attractor dynamics - Andrew Nam; Eric Elmoznino; Nikolay Malkin; Chen Sun; Yoshua Bengio; Guillaume Lajoie (CoRR, 2023)

Leveraging Diffusion Disentangled Representations to Mitigate Shortcuts in Underspecified Visual Tasks - Luca Scimeca; Alexander Rubinstein; Armand Mihai Nicolicioiu; Damien Teney; Yoshua Bengio (CoRR, 2023)

Delta-AI: Local objectives for amortized inference in sparse graphical models - Jean-Pierre R. Falet; Hae Beom Lee; Nikolay Malkin; Chen Sun; Dragos Secrieru; Dinghuai Zhang; Guillaume Lajoie; Yoshua Bengio (CoRR, 2023)

Diffusion Generative Flow Samplers: Improving learning signals through partial trajectory optimization - Dinghuai Zhang; Ricky Tian Qi Chen; Cheng-Hao Liu; Aaron C. Courville; Yoshua Bengio (CoRR, 2023)

Local Search GFlowNets - Minsu Kim; Taeyoung Yun; Emmanuel Bengio; Dinghuai Zhang; Yoshua Bengio; Sungsoo Ahn; Jinkyoo Park (CoRR, 2023)

Expected flow networks in stochastic environments and two-player zero-sum games - Marco Jiralerspong; Bilun Sun; Danilo Vucetic; Tianyu Zhang; Yoshua Bengio; Gauthier Gidel; Nikolay Malkin (CoRR, 2023)

Learning to Scale Logits for Temperature-Conditional GFlowNets - Minsu Kim; Joohwan Ko; Dinghuai Zhang; Ling Pan; Taeyoung Yun; Woochang Kim; Jinkyoo Park; Yoshua Bengio (CoRR, 2023)

Pre-Training and Fine-Tuning Generative Flow Networks - Ling Pan; Moksh Jain; Kanika Madan; Yoshua Bengio (CoRR, 2023)

Causal Inference in Gene Regulatory Networks with GFlowNet: Towards Scalability in Large Systems - Bailey Trang Nguyen; Alexander Tong; Kanika Madan; Yoshua Bengio; Dianbo Liu (CoRR, 2023)

Amortizing intractable inference in large language models - Edward J. Hu; Moksh Jain; Eric Elmoznino; Younesse Kaddar; Guillaume Lajoie; Yoshua Bengio; Nikolay Malkin (CoRR, 2023)

Crystal-GFN: sampling crystals with desirable properties and constraints - Alex Hernández-García; Alexandre Duval; Alexandra Volokhova; Yoshua Bengio; Divya Sharma; Pierre Luc Carrier; Michal Koziarski; Victor Schmidt (CoRR, 2023)

On the importance of catalyst-adsorbate 3D interactions for relaxed energy predictions - Alvaro Carbonero; Alexandre Duval; Victor Schmidt; Santiago Miret; Alex Hernández-García; Yoshua Bengio; David Rolnick (CoRR, 2023)

A cry for help: Early detection of brain injury in newborns - Charles C. Onu; Samantha Latremouille; Arsenii Gorin; Junhao Wang; Uchenna Ekwochi; Peter O. Ubuane; Omolara A. Kehinde; Muhammad A. Salisu; Datonye Briggs; Yoshua Bengio; Doina Precup (CoRR, 2023)

PhyloGFN: Phylogenetic inference with generative flow networks - Mingyang Zhou; Zichao Yan; Elliot Layne; Nikolay Malkin; Dinghuai Zhang; Moksh Jain; Mathieu Blanchette; Yoshua Bengio (CoRR, 2023)

Towards equilibrium molecular conformation generation with GFlowNets - Alexandra Volokhova; Michal Koziarski; Alex Hernández-García; Cheng-Hao Liu; Santiago Miret; Pablo Lemos; Luca A. Thiede; Zichao Yan; Alán Aspuru-Guzik; Yoshua Bengio (CoRR, 2023)

Causal machine learning for single-cell genomics - Alejandro Tejada-Lapuerta; Paul Bertin; Stefan Bauer; Hananeh Aliee; Yoshua Bengio; Fabian J. Theis (CoRR, 2023)

Managing AI Risks in an Era of Rapid Progress - Yoshua Bengio; Geoffrey E. Hinton; Andrew Yao; Dawn Song; Pieter Abbeel; Yuval Noah Harari; Ya-Qin Zhang; Lan Xue; Shai Shalev-Shwartz; Gillian K. Hadfield; Jeff Clune; Tegan Maharaj; et al. (CoRR, 2023)

Laughing Hyena Distillery: Extracting Compact Recurrences From Convolutions - Stefano Massaroli; Michael Poli; Daniel Y. Fu; Hermann Kumbong; Rom N. Parnichkun; Aman Timalsina; David W. Romero; Quinn McIntyre; Beidi Chen; Atri Rudra; Ce Zhang; Christopher Ré; et al. (CoRR, 2023)

OC-NMN: Object-centric Compositional Neural Module Network for Generative Visual Analogical Reasoning - Rim Assouel; Pau Rodríguez; Perouz Taslakian; David Vázquez; Yoshua Bengio (CoRR, 2023)

Object-centric architectures enable efficient causal representation learning - Amin Mansouri; Jason S. Hartford; Yan Zhang; Yoshua Bengio (CoRR, 2023)

SatBird: Bird Species Distribution Modeling with Remote Sensing and Citizen Science Data - Mélisande Teng; Amna Elmustafa; Benjamin Akera; Yoshua Bengio; Hager Radi Abdelwahed; Hugo Larochelle; David Rolnick (CoRR, 2023)

Unlearning via Sparse Representations - Vedant Shah; Frederik Träuble; Ashish Malik; Hugo Larochelle; Michael Mozer; Sanjeev Arora; Yoshua Bengio; Anirudh Goyal (CoRR, 2023)

Shortcut Bias Mitigation via Ensemble Diversity Using Diffusion Probabilistic Models - Luca Scimeca; Alexander Rubinstein; Damien Teney; Seong Joon Oh; Armand Mihai Nicolicioiu; Yoshua Bengio (CoRR, 2023)

Improving Gradient-guided Nested Sampling for Posterior Inference - Pablo Lemos; Nikolay Malkin; Will Handley; Yoshua Bengio; Yashar Hezaveh; Laurence Perreault Levasseur (CoRR, 2023)

A Hitchhiker's Guide to Geometric GNNs for 3D Atomic Systems - Alexandre Duval; Simon V. Mathis; Chaitanya K. Joshi; Victor Schmidt; Santiago Miret; Fragkiskos D. Malliaros; Taco Cohen; Pietro Lio; Yoshua Bengio; Michael M. Bronstein (CoRR, 2023)

Predicting Tactical Solutions to Operational Planning Problems Under Imperfect Information - Eric Larsen; Sébastien Lachapelle; Yoshua Bengio; Emma Frejinger; Simon Lacoste-Julien; Andrea Lodi (INFORMS J. Comput., 2022)

RetroGNN: Fast Estimation of Synthesizability for Virtual Screening and De Novo Design by Learning from Slow Retrosynthesis Software - Cheng-Hao Liu; Maksym Korablyov; Stanislaw Jastrzebski; Pawel Wlodarczyk-Pruszynski; Yoshua Bengio; Marwin H. S. Segler (J. Chem. Inf. Model., 2022)

Interpolation consistency training for semi-supervised learning - Vikas Verma; Kenji Kawaguchi; Alex Lamb; Juho Kannala; Arno Solin; Yoshua Bengio; David Lopez-Paz (Neural Networks, 2022)

Interpolated Adversarial Training: Achieving robust neural networks without sacrificing too much accuracy - Alex Lamb; Vikas Verma; Kenji Kawaguchi; Alexander Matyasko; Savya Khosla; Juho Kannala; Yoshua Bengio (Neural Networks, 2022)

Lookback for Learning to Branch - Prateek Gupta; Elias Boutros Khalil; Didier Chételat; Maxime Gasse; Andrea Lodi; Yoshua Bengio; M. Pawan Kumar (Trans. Mach. Learn. Res., 2022)

A Two-Stream Continual Learning System With Variational Domain-Agnostic Feature Replay - Qicheng Lao; Xiang Jiang; Mohammad Havaei; Yoshua Bengio (IEEE Trans. Neural Networks Learn. Syst., 2022)

PMFL: Partial Meta-Federated Learning for heterogeneous tasks and its applications on real-world medical records - Tianyi Zhang; Shirui Zhang; Ziwei Chen; Yoshua Bengio; Dianbo Liu (IEEE International Conference on Big Data, Big Data 2022, Osaka, Japan, December 17-20, 2022, 2022)

VIM: Variational Independent Modules for Video Prediction - Rim Assouel; Lluís Castrejón; Aaron C. Courville; Nicolas Ballas; Yoshua Bengio (1st Conference on Causal Learning and Reasoning, CLeaR 2022, Sequoia Conference Center, Eureka, CA, USA, 11-13 April, 2022, 2022)

Properties from mechanisms: an equivariance perspective on identifiable representation learning - Kartik Ahuja; Jason S. Hartford; Yoshua Bengio (The Tenth International Conference on Learning Representations, ICLR 2022, Virtual Event, April 25-29, 2022, 2022)

Continuous-Time Meta-Learning with Forward Mode Differentiation - Tristan Deleu; David Kanaa; Leo Feng; Giancarlo Kerg; Yoshua Bengio; Guillaume Lajoie; Pierre-Luc Bacon (The Tenth International Conference on Learning Representations, ICLR 2022, Virtual Event, April 25-29, 2022, 2022)

Graph Neural Networks with Learnable Structural and Positional Representations - Vijay Prakash Dwivedi; Anh Tuan Luu; Thomas Laurent; Yoshua Bengio; Xavier Bresson (The Tenth International Conference on Learning Representations, ICLR 2022, Virtual Event, April 25-29, 2022, 2022)

Coordination Among Neural Modules Through a Shared Global Workspace - Anirudh Goyal; Aniket Rajiv Didolkar; Alex Lamb; Kartikeya Badola; Nan Rosemary Ke; Nasim Rahaman; Jonathan Binas; Charles Blundell; Michael Curtis Mozer; Yoshua Bengio (The Tenth International Conference on Learning Representations, ICLR 2022, Virtual Event, April 25-29, 2022, 2022)

Compositional Attention: Disentangling Search and Retrieval - Sarthak Mittal; Sharath Chandra Raparthy; Irina Rish; Yoshua Bengio; Guillaume Lajoie (The Tenth International Conference on Learning Representations, ICLR 2022, Virtual Event, April 25-29, 2022, 2022)

Chunked Autoregressive GAN for Conditional Waveform Synthesis - Max Morrison; Rithesh Kumar; Kundan Kumar; Prem Seetharaman; Aaron C. Courville; Yoshua Bengio (The Tenth International Conference on Learning Representations, ICLR 2022, Virtual Event, April 25-29, 2022, 2022)

ClimateGAN: Raising Climate Change Awareness by Generating Images of Floods - Victor Schmidt; Alexandra Luccioni; Mélisande Teng; Tianyu Zhang; Alexia Reynaud; Sunand Raghupathi; Gautier Cosne; Adrien Juraver; Vahe Vardanyan; Alex Hernández-García; Yoshua Bengio (The Tenth International Conference on Learning Representations, ICLR 2022, Virtual Event, April 25-29, 2022, 2022)

Unifying Likelihood-free Inference with Black-box Optimization and Beyond - Dinghuai Zhang; Jie Fu; Yoshua Bengio; Aaron C. Courville (The Tenth International Conference on Learning Representations, ICLR 2022, Virtual Event, April 25-29, 2022, 2022)

Towards Scaling Difference Target Propagation by Learning Backprop Targets - Maxence Ernoult; Fabrice Normandin; Abhinav Moudgil; Sean Spinney; Eugene Belilovsky; Irina Rish; Blake A. Richards; Yoshua Bengio (International Conference on Machine Learning, ICML 2022, 17-23 July 2022, Baltimore, Maryland, USA, 2022)

Biological Sequence Design with GFlowNets - Moksh Jain; Emmanuel Bengio; Alex Hernández-García; Jarrid Rector-Brooks; Bonaventure F. P. Dossou; Chanakya Ajit Ekbote; Jie Fu; Tianyu Zhang; Michael Kilgour; Dinghuai Zhang; Lena Simine; Payel Das; et al. (International Conference on Machine Learning, ICML 2022, 17-23 July 2022, Baltimore, Maryland, USA, 2022)

Multi-scale Feature Learning Dynamics: Insights for Double Descent - Mohammad Pezeshki; Amartya Mitra; Yoshua Bengio; Guillaume Lajoie (International Conference on Machine Learning, ICML 2022, 17-23 July 2022, Baltimore, Maryland, USA, 2022)

Generative Flow Networks for Discrete Probabilistic Modeling - Dinghuai Zhang; Nikolay Malkin; Zhen Liu; Alexandra Volokhova; Aaron C. Courville; Yoshua Bengio (International Conference on Machine Learning, ICML 2022, 17-23 July 2022, Baltimore, Maryland, USA, 2022)

Building Robust Ensembles via Margin Boosting - Dinghuai Zhang; Hongyang Zhang; Aaron C. Courville; Yoshua Bengio; Pradeep Ravikumar; Arun Sai Suggala (International Conference on Machine Learning, ICML 2022, 17-23 July 2022, Baltimore, Maryland, USA, 2022)

Weakly Supervised Representation Learning with Sparse Perturbations - Kartik Ahuja; Jason S. Hartford; Yoshua Bengio (Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, NeurIPS 2022, New Orleans, LA, USA, November 28 - December 9, 2022, 2022)

MAgNet: Mesh Agnostic Neural PDE Solver - Oussama Boussif; Yoshua Bengio; Loubna Benabbou; Dan Assouline (Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, NeurIPS 2022, New Orleans, LA, USA, November 28 - December 9, 2022, 2022)

Temporal Latent Bottleneck: Synthesis of Fast and Slow Processing Mechanisms in Sequence Learning - Aniket Didolkar; Kshitij Gupta; Anirudh Goyal; Nitesh B. Gundavarapu; Alex Lamb; Nan Rosemary Ke; Yoshua Bengio (Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, NeurIPS 2022, New Orleans, LA, USA, November 28 - December 9, 2022, 2022)

Controlled Sparsity via Constrained Optimization or: How I Learned to Stop Tuning Penalties and Love Constraints - Jose Gallego-Posada; Juan Ramirez; Akram Erraqabi; Yoshua Bengio; Simon Lacoste-Julien (Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, NeurIPS 2022, New Orleans, LA, USA, November 28 - December 9, 2022, 2022)

Discrete Compositional Representations as an Abstraction for Goal Conditioned Reinforcement Learning - Riashat Islam; Hongyu Zang; Anirudh Goyal; Alex Lamb; Kenji Kawaguchi; Xin Li; Romain Laroche; Yoshua Bengio; Remi Tachet des Combes (Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, NeurIPS 2022, New Orleans, LA, USA, November 28 - December 9, 2022, 2022)

Trajectory balance: Improved credit assignment in GFlowNets - Nikolay Malkin; Moksh Jain; Emmanuel Bengio; Chen Sun; Yoshua Bengio (Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, NeurIPS 2022, New Orleans, LA, USA, November 28 - December 9, 2022, 2022)

Is a Modular Architecture Enough? - Sarthak Mittal; Yoshua Bengio; Guillaume Lajoie (Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, NeurIPS 2022, New Orleans, LA, USA, November 28 - December 9, 2022, 2022)

Neural Attentive Circuits - Martin Weiss; Nasim Rahaman; Francesco Locatello; Chris Pal; Yoshua Bengio; Bernhard Schölkopf; Li Erran Li; Nicolas Ballas (Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, NeurIPS 2022, New Orleans, LA, USA, November 28 - December 9, 2022, 2022)

Bayesian structure learning with generative flow networks - Tristan Deleu; António Góis; Chris Emezue; Mansi Rankawat; Simon Lacoste-Julien; Stefan Bauer; Yoshua Bengio (Uncertainty in Artificial Intelligence, Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, UAI 2022, 1-5 August 2022, Eindhoven, The Netherlands, 2022)

Temporal abstractions-augmented temporally contrastive learning: An alternative to the Laplacian in RL - Akram Erraqabi; Marlos C. Machado; Mingde Zhao; Sainbayar Sukhbaatar; Alessandro Lazaric; Ludovic Denoyer; Yoshua Bengio (Uncertainty in Artificial Intelligence, Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, UAI 2022, 1-5 August 2022, Eindhoven, The Netherlands, 2022)

The Effect of Diversity in Meta-Learning - Ramnath Kumar; Tristan Deleu; Yoshua Bengio (CoRR, 2022)

Rethinking Learning Dynamics in RL using Adversarial Networks - Ramnath Kumar; Tristan Deleu; Yoshua Bengio (CoRR, 2022)

Trajectory Balance: Improved Credit Assignment in GFlowNets - Nikolay Malkin; Moksh Jain; Emmanuel Bengio; Chen Sun; Yoshua Bengio (CoRR, 2022)

Towards Scaling Difference Target Propagation by Learning Backprop Targets - Maxence Ernoult; Fabrice Normandin; Abhinav Moudgil; Sean Spinney; Eugene Belilovsky; Irina Rish; Blake A. Richards; Yoshua Bengio (CoRR, 2022)

Adaptive Discrete Communication Bottlenecks with Dynamic Vector Quantization - Dianbo Liu; Alex Lamb; Xu Ji; Pascal Notsawo; Michael Mozer; Yoshua Bengio; Kenji Kawaguchi (CoRR, 2022)

Generative Flow Networks for Discrete Probabilistic Modeling - Dinghuai Zhang; Nikolay Malkin; Zhen Liu; Alexandra Volokhova; Aaron C. Courville; Yoshua Bengio (CoRR, 2022)

RECOVER: sequential model optimization platform for combination drug repurposing identifies novel synergistic compounds in vitro - Paul Bertin; Jarrid Rector-Brooks; Deepak Sharma; Thomas Gaudelet; Andrew Anighoro; Torsten Gross; Francisco Martinez-Pena; Eileen L. Tang; Suraj M. S; Cristian Regep; Jeremy B. R. Hayter; Maksym Korablyov; et al. (CoRR, 2022)

Bayesian Structure Learning with Generative Flow Networks - Tristan Deleu; António Góis; Chris Emezue; Mansi Rankawat; Simon Lacoste-Julien; Stefan Bauer; Yoshua Bengio (CoRR, 2022)

Continuous-Time Meta-Learning with Forward Mode Differentiation - Tristan Deleu; David Kanaa; Leo Feng; Giancarlo Kerg; Yoshua Bengio; Guillaume Lajoie; Pierre-Luc Bacon (CoRR, 2022)

A New Era: Intelligent Tutoring Systems Will Transform Online Learning for Millions - François St-Hilaire; Dung Do Vu; Antoine Frau; Nathan Burns; Farid Faraji; Joseph Potochny; Stephane Robert; Arnaud Roussel; Selene Zheng; Taylor Glazier; Junfel Vincent Romano; Robert Belfer; et al. (CoRR, 2022)

Biological Sequence Design with GFlowNets - Moksh Jain; Emmanuel Bengio; Alex Hernández-García; Jarrid Rector-Brooks; Bonaventure F. P. Dossou; Chanakya Ekbote; Jie Fu; Tianyu Zhang; Michael Kilgour; Dinghuai Zhang; Lena Simine; Payel Das; et al. (CoRR, 2022)

Temporal Abstractions-Augmented Temporally Contrastive Learning: An Alternative to the Laplacian in RL - Akram Erraqabi; Marlos C. Machado; Mingde Zhao; Sainbayar Sukhbaatar; Alessandro Lazaric; Ludovic Denoyer; Yoshua Bengio (CoRR, 2022)

(Private)-Retroactive Carbon Pricing [(P)ReCaP]: A Market-based Approach for Climate Finance and Risk Assessment - Yoshua Bengio; Prateek Gupta; Dylan R. Radovic; Maarten Scholl; Andrew Williams; Christian Schröder de Witt; Tianyu Zhang; Yang Zhang (CoRR, 2022)

A Highly Adaptive Acoustic Model for Accurate Multi-Dialect Speech Recognition - Sanghyun Yoo; Inchul Song; Yoshua Bengio (CoRR, 2022)

FedILC: Weighted Geometric Mean and Invariant Gradient Covariance for Federated Learning on Non-IID Data - Mike He Zhu; Léna Néhale Ezzine; Dianbo Liu; Yoshua Bengio (CoRR, 2022)

Coordinating Policies Among Multiple Agents via an Intelligent Communication Channel - Dianbo Liu; Vedant Shah; Oussama Boussif; Cristian Meo; Anirudh Goyal; Tianmin Shu; Michael Mozer; Nicolas Heess; Yoshua Bengio (CoRR, 2022)

FL Games: A federated learning framework for distribution shifts - Sharut Gupta; Kartik Ahuja; Mohammad Havaei; Niladri Chatterjee; Yoshua Bengio (CoRR, 2022)

Temporal Latent Bottleneck: Synthesis of Fast and Slow Processing Mechanisms in Sequence Learning - Aniket Didolkar; Kshitij Gupta; Anirudh Goyal; Alex Lamb; Nan Rosemary Ke; Yoshua Bengio (CoRR, 2022)

Agnostic Physics-Driven Deep Learning - Benjamin Scellier; Siddhartha Mishra; Yoshua Bengio; Yann Ollivier (CoRR, 2022)

Weakly Supervised Representation Learning with Sparse Perturbations - Kartik Ahuja; Jason S. Hartford; Yoshua Bengio (CoRR, 2022)

Is a Modular Architecture Enough? - Sarthak Mittal; Yoshua Bengio; Guillaume Lajoie (CoRR, 2022)

Building Robust Ensembles via Margin Boosting - Dinghuai Zhang; Hongyang Zhang; Aaron C. Courville; Yoshua Bengio; Pradeep Ravikumar; Arun Sai Suggala (CoRR, 2022)

On the Generalization and Adaption Performance of Causal Models - Nino Scherrer; Anirudh Goyal; Stefan Bauer; Yoshua Bengio; Nan Rosemary Ke (CoRR, 2022)

On Neural Architecture Inductive Biases for Relational Tasks - Giancarlo Kerg; Sarthak Mittal; David Rolnick; Yoshua Bengio; Blake A. Richards; Guillaume Lajoie (CoRR, 2022)

Your Autoregressive Generative Model Can be Better If You Treat It as an Energy-Based One - Yezhen Wang; Tong Che; Bo Li; Kaitao Song; Hengzhi Pei; Yoshua Bengio; Dongsheng Li (CoRR, 2022)

Lookback for Learning to Branch - Prateek Gupta; Elias B. Khalil; Didier Chételat; Maxime Gasse; Yoshua Bengio; Andrea Lodi; M. Pawan Kumar (CoRR, 2022)

Discrete Key-Value Bottleneck - Frederik Träuble; Anirudh Goyal; Nasim Rahaman; Michael Mozer; Kenji Kawaguchi; Yoshua Bengio; Bernhard Schölkopf (CoRR, 2022)

Controlled Sparsity via Constrained Optimization or: How I Learned to Stop Tuning Penalties and Love Constraints - Jose Gallego-Posada; Juan Ramirez; Akram Erraqabi; Yoshua Bengio; Simon Lacoste-Julien (CoRR, 2022)

Diversifying Design of Nucleic Acid Aptamers Using Unsupervised Machine Learning - Siba Moussa; Michael Kilgour; Clara Jans; Alex Hernández-García; Miroslava Cuperlovic-Culf; Yoshua Bengio; Lena Simine (CoRR, 2022)

AI for Global Climate Cooperation: Modeling Global Climate Negotiations, Agreements, and Long-Term Cooperation in RICE-N - Tianyu Zhang; Andrew Williams; Soham Phade; Sunil Srinivasa; Yang Zhang; Prateek Gupta; Yoshua Bengio; Stephan Zheng (CoRR, 2022)

Unifying Generative Models with GFlowNets - Dinghuai Zhang; Ricky T. Q. Chen; Nikolay Malkin; Yoshua Bengio (CoRR, 2022)

Designing Biological Sequences via Meta-Reinforcement Learning and Bayesian Optimization - Leo Feng; Padideh Nouri; Aneri Muni; Yoshua Bengio; Pierre-Luc Bacon (CoRR, 2022)

Interventional Causal Representation Learning - Kartik Ahuja; Yixin Wang; Divyat Mahajan; Yoshua Bengio (CoRR, 2022)

Learning GFlowNets from partial episodes for improved convergence and stability - Kanika Madan; Jarrid Rector-Brooks; Maksym Korablyov; Emmanuel Bengio; Moksh Jain; Andrei Cristian Nica; Tom Bosc; Yoshua Bengio; Nikolay Malkin (CoRR, 2022)

Graph-Based Active Machine Learning Method for Diverse and Novel Antimicrobial Peptides Generation and Selection - Bonaventure F. P. Dossou; Dianbo Liu; Xu Ji; Moksh Jain; Almer M. van der Sloot; Roger Palou; Michael Tyers; Yoshua Bengio (CoRR, 2022)

Predictive Inference with Feature Conformal Prediction - Jiaye Teng; Chuan Wen; Dinghuai Zhang; Yoshua Bengio; Yang Gao; Yang Yuan (CoRR, 2022)

GFlowNets and variational inference - Nikolay Malkin; Salem Lahlou; Tristan Deleu; Xu Ji; Edward J. Hu; Katie Everett; Dinghuai Zhang; Yoshua Bengio (CoRR, 2022)

Latent State Marginalization as a Low-cost Approach for Improving Exploration - Dinghuai Zhang; Aaron C. Courville; Yoshua Bengio; Qinqing Zheng; Amy Zhang; Ricky T. Q. Chen (CoRR, 2022)

Stateful active facilitator: Coordination and Environmental Heterogeneity in Cooperative Multi-Agent Reinforcement Learning - Dianbo Liu; Vedant Shah; Oussama Boussif; Cristian Meo; Anirudh Goyal; Tianmin Shu; Michael Mozer; Nicolas Heess; Yoshua Bengio (CoRR, 2022)

Generative Augmented Flow Networks - Ling Pan; Dinghuai Zhang; Aaron C. Courville; Longbo Huang; Yoshua Bengio (CoRR, 2022)

MAgNet: Mesh Agnostic Neural PDE Solver - Oussama Boussif; Dan Assouline; Loubna Benabbou; Yoshua Bengio (CoRR, 2022)

Robust and Controllable Object-Centric Learning through Energy-based Models - Ruixiang Zhang; Tong Che; Boris Ivanovic; Renhao Wang; Marco Pavone; Yoshua Bengio; Liam Paull (CoRR, 2022)

Contrastive introspection (ConSpec) to rapidly identify invariant steps for success - Chen Sun; Wannan Yang; Benjamin Alsbury-Nealy; Yoshua Bengio; Blake A. Richards (CoRR, 2022)

Neural Attentive Circuits - Nasim Rahaman; Martin Weiss; Francesco Locatello; Chris Pal; Yoshua Bengio; Bernhard Schölkopf; Li Erran Li; Nicolas Ballas (CoRR, 2022)

Toward Next-Generation Artificial Intelligence: Catalyzing the NeuroAI Revolution - Anthony Zador; Blake A. Richards; Bence Ölveczky; Sean Escola; Yoshua Bengio; Kwabena Boahen; Matthew M. Botvinick; Dmitri B. Chklovskii; Anne Churchland; Claudia Clopath; James DiCarlo; Surya Ganguli; et al. (CoRR, 2022)

Multi-Objective GFlowNets - Moksh Jain; Sharath Chandra Raparthy; Alex Hernández-García; Jarrid Rector-Brooks; Yoshua Bengio; Santiago Miret; Emmanuel Bengio (CoRR, 2022)

GFlowOut: Dropout with Generative Flow Networks - Dianbo Liu; Moksh Jain; Bonaventure Dossou; Qianli Shen; Salem Lahlou; Anirudh Goyal; Nikolay Malkin; Chris Emezue; Dinghuai Zhang; Nadhir Hassen; Xu Ji; Kenji Kawaguchi; et al. (CoRR, 2022)

FL Games: A Federated Learning Framework for Distribution Shifts - Sharut Gupta; Kartik Ahuja; Mohammad Havaei; Niladri Chatterjee; Yoshua Bengio (CoRR, 2022)

Discrete Factorial Representations as an Abstraction for Goal Conditioned Reinforcement Learning - Riashat Islam; Hongyu Zang; Anirudh Goyal; Alex Lamb; Kenji Kawaguchi; Xin Li; Romain Laroche; Yoshua Bengio; Remi Tachet des Combes (CoRR, 2022)

Consistent Training via Energy-Based GFlowNets for Modeling Discrete Joint Distributions - Chanakya Ekbote; Moksh Jain; Payel Das; Yoshua Bengio (CoRR, 2022)

A General Purpose Neural Architecture for Geospatial Systems - Nasim Rahaman; Martin Weiss; Frederik Träuble; Francesco Locatello; Alexandre Lacoste; Yoshua Bengio; Chris Pal; Li Erran Li; Bernhard Schölkopf (CoRR, 2022)

Bayesian learning of Causal Structure and Mechanisms with GFlowNets and Variational Bayes - Mizu Nishikawa-Toomey; Tristan Deleu; Jithendaraa Subramanian; Yoshua Bengio; Laurent Charlin (CoRR, 2022)

Posterior samples of source galaxies in strong gravitational lenses with score-based priors - Alexandre Adam; Adam Coogan; Nikolay Malkin; Ronan Legin; Laurence Perreault Levasseur; Yashar Hezaveh; Yoshua Bengio (CoRR, 2022)

Equivariance with Learned Canonicalization Functions - Sékou-Oumar Kaba; Arnab Kumar Mondal; Yan Zhang; Yoshua Bengio; Siamak Ravanbakhsh (CoRR, 2022)

Latent Bottlenecked Attentive Neural Processes - Leo Feng; Hossein Hajimirsadeghi; Yoshua Bengio; Mohamed Osama Ahmed (CoRR, 2022)

PhAST: Physics-Aware, Scalable, and Task-specific GNNs for Accelerated Catalyst Design - Alexandre Duval; Victor Schmidt; Santiago Miret; Yoshua Bengio; Alex Hernández-García; David Rolnick (CoRR, 2022)

Synergies Between Disentanglement and Sparsity: a Multi-Task Learning Perspective - Sébastien Lachapelle; Tristan Deleu; Divyat Mahajan; Ioannis Mitliagkas; Yoshua Bengio; Simon Lacoste-Julien; Quentin Bertrand (CoRR, 2022)

MixupE: Understanding and Improving Mixup from Directional Derivative Perspective - Vikas Verma; Sarthak Mittal; Wai Hoh Tang; Hieu Pham; Juho Kannala; Yoshua Bengio; Arno Solin; Kenji Kawaguchi (CoRR, 2022)

Deep learning for AI - Yoshua Bengio; Yann LeCun; Geoffrey E. Hinton (Commun. ACM, 2021)

Using Artificial Intelligence to Visualize the Impacts of Climate Change - Alexandra Luccioni; Victor Schmidt; Vahe Vardanyan; Yoshua Bengio; Theresa-Marie Rhyne (IEEE Computer Graphics and Applications, 2021)

Machine learning for combinatorial optimization: A methodological tour d'horizon - Yoshua Bengio; Andrea Lodi; Antoine Prouvost (Eur. J. Oper. Res., 2021)

Inherent privacy limitations of decentralized contact tracing apps - Yoshua Bengio; Daphne Ippolito; Richard Janda; Max Jarvie; Benjamin Prud'homme; Jean-Franois Rousseau; Abhinav Sharma; Yun William Yu (J. Am. Medical Informatics Assoc., 2021)

Toward Causal Representation Learning - Bernhard Schölkopf; Francesco Locatello; Stefan Bauer; Nan Rosemary Ke; Nal Kalchbrenner; Anirudh Goyal; Yoshua Bengio (Proc. IEEE, 2021)

CAMAP: Artificial neural networks unveil the role of codon arrangement in modulating MHC-I peptides presentation - Tariq Daouda; Maude Dumont-Lagacé; Albert Feghaly; Yahya Benslimane; Rébecca Panes; Mathieu Courcelles; Mohamed Benhammadi; Lea Harrington; Pierre Thibault; François Major; Yoshua Bengio; Etienne Gagnon; et al. (PLoS Comput. Biol., 2021)

Object-Centric Image Generation from Layouts - Tristan Sylvain; Pengchuan Zhang; Yoshua Bengio; R. Devon Hjelm; Shikhar Sharma (Thirty-Fifth AAAI Conference on Artificial Intelligence, AAAI 2021, Thirty-Third Conference on Innovative Applications of Artificial Intelligence, IAAI 2021, The Eleventh Symposium on Educational Advances in Artificial Intelligence, EAAI 2021, Virtual Event, February 2-9, 2021, 2021)

Parameterizing Branch-and-Bound Search Trees to Learn Branching Policies - Giulia Zarpellon; Jason Jo; Andrea Lodi; Yoshua Bengio (Thirty-Fifth AAAI Conference on Artificial Intelligence, AAAI 2021, Thirty-Third Conference on Innovative Applications of Artificial Intelligence, IAAI 2021, The Eleventh Symposium on Educational Advances in Artificial Intelligence, EAAI 2021, Virtual Event, February 2-9, 2021, 2021)

Deep Verifier Networks: Verification of Deep Discriminative Models with Deep Generative Models - Tong Che; Xiaofeng Liu; Site Li; Yubin Ge; Ruixiang Zhang; Caiming Xiong; Yoshua Bengio (Thirty-Fifth AAAI Conference on Artificial Intelligence, AAAI 2021, Thirty-Third Conference on Innovative Applications of Artificial Intelligence, IAAI 2021, The Eleventh Symposium on Educational Advances in Artificial Intelligence, EAAI 2021, Virtual Event, February 2-9, 2021, 2021)

Visual Concept Reasoning Networks - Taesup Kim; Sungwoong Kim; Yoshua Bengio (Thirty-Fifth AAAI Conference on Artificial Intelligence, AAAI 2021, Thirty-Third Conference on Innovative Applications of Artificial Intelligence, IAAI 2021, The Eleventh Symposium on Educational Advances in Artificial Intelligence, EAAI 2021, Virtual Event, February 2-9, 2021, 2021)

Meta-Learning Framework with Applications to Zero-Shot Time-Series Forecasting - Boris N. Oreshkin; Dmitri Carpov; Nicolas Chapados; Yoshua Bengio (Thirty-Fifth AAAI Conference on Artificial Intelligence, AAAI 2021, Thirty-Third Conference on Innovative Applications of Artificial Intelligence, IAAI 2021, The Eleventh Symposium on Educational Advances in Artificial Intelligence, EAAI 2021, Virtual Event, February 2-9, 2021, 2021)

GraphMix: Improved Training of GNNs for Semi-Supervised Learning - Vikas Verma; Meng Qu; Kenji Kawaguchi; Alex Lamb; Yoshua Bengio; Juho Kannala; Jian Tang (Thirty-Fifth AAAI Conference on Artificial Intelligence, AAAI 2021, Thirty-Third Conference on Innovative Applications of Artificial Intelligence, IAAI 2021, The Eleventh Symposium on Educational Advances in Artificial Intelligence, EAAI 2021, Virtual Event, February 2-9, 2021, 2021)

A Comparative Study of Learning Outcomes for Online Learning Platforms - François St-Hilaire; Nathan Burns; Robert Belfer; Muhammad Shayan; Ariella Smofsky; Dung Do Vu; Antoine Frau; Joseph Potochny; Farid Faraji; Vincent Pavero; Neroli Ko; Ansona Onyi Ching; et al. (Artificial Intelligence in Education - 22nd International Conference, AIED 2021, Utrecht, The Netherlands, June 14-18, 2021, Proceedings, Part II, 2021)

An Analysis of the Adaptation Speed of Causal Models - Rémi Le Priol; Reza Babanezhad; Yoshua Bengio; Simon Lacoste-Julien (The 24th International Conference on Artificial Intelligence and Statistics, AISTATS 2021, April 13-15, 2021, Virtual Event, 2021)

Neural Function Modules with Sparse Arguments: A Dynamic Approach to Integrating Information across Layers - Alex Lamb; Anirudh Goyal; Agnieszka Slowik; Michael Mozer; Philippe Beaudoin; Yoshua Bengio (The 24th International Conference on Artificial Intelligence and Statistics, AISTATS 2021, April 13-15, 2021, Virtual Event, 2021)

CMIM: Cross-Modal Information Maximization For Medical Imaging - Tristan Sylvain; Francis Dutil; Tess Berthier; Lisa Di-Jorio; Margaux Luck; R. Devon Hjelm; Yoshua Bengio (IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2021, Toronto, ON, Canada, June 6-11, 2021, 2021)

FloW: A Dataset and Benchmark for Floating Waste Detection in Inland Waters - Yuwei Cheng; Jiannan Zhu; Mengxin Jiang; Jie Fu; Changsong Pang; Peidong Wang; Kris Sankaran; Olawale Onabola; Yimin Liu; Dianbo Liu; Yoshua Bengio (2021 IEEE/CVF International Conference on Computer Vision, ICCV 2021, Montreal, QC, Canada, October 10-17, 2021, 2021)

Systematic generalisation with group invariant predictions - Faruk Ahmed; Yoshua Bengio; Harm van Seijen; Aaron C. Courville (9th International Conference on Learning Representations, ICLR 2021, Virtual Event, Austria, May 3-7, 2021, 2021)

CausalWorld: A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning - Ossama Ahmed; Frederik Träuble; Anirudh Goyal; Alexander Neitz; Manuel Wuthrich; Yoshua Bengio; Bernhard Schölkopf; Stefan Bauer (9th International Conference on Learning Representations, ICLR 2021, Virtual Event, Austria, May 3-7, 2021, 2021)

Predicting Infectiousness for Proactive Contact Tracing - Yoshua Bengio; Prateek Gupta; Tegan Maharaj; Nasim Rahaman; Martin Weiss; Tristan Deleu; Eilif Benjamin Müller; Meng Qu; Victor Schmidt; Pierre-Luc St-Charles; Hannah Alsdurf; Olexa Bilaniuk; et al. (9th International Conference on Learning Representations, ICLR 2021, Virtual Event, Austria, May 3-7, 2021, 2021)

Factorizing Declarative and Procedural Knowledge in Structured, Dynamical Environments - Anirudh Goyal; Alex Lamb; Phanideep Gampa; Philippe Beaudoin; Charles Blundell; Sergey Levine; Yoshua Bengio; Michael Curtis Mozer (9th International Conference on Learning Representations, ICLR 2021, Virtual Event, Austria, May 3-7, 2021, 2021)

Recurrent Independent Mechanisms - Anirudh Goyal; Alex Lamb; Jordan Hoffmann; Shagun Sodhani; Sergey Levine; Yoshua Bengio; Bernhard Schölkopf (9th International Conference on Learning Representations, ICLR 2021, Virtual Event, Austria, May 3-7, 2021, 2021)

Fast And Slow Learning Of Recurrent Independent Mechanisms - Kanika Madan; Nan Rosemary Ke; Anirudh Goyal; Bernhard Schölkopf; Yoshua Bengio (9th International Conference on Learning Representations, ICLR 2021, Virtual Event, Austria, May 3-7, 2021, 2021)

RNNLogic: Learning Logic Rules for Reasoning on Knowledge Graphs - Meng Qu; Jun-Kun Chen; Louis-Pascal A. C. Xhonneux; Yoshua Bengio; Jian Tang (9th International Conference on Learning Representations, ICLR 2021, Virtual Event, Austria, May 3-7, 2021, 2021)

Spatially Structured Recurrent Modules - Nasim Rahaman; Anirudh Goyal; Muhammad Waleed Gondal; Manuel Wuthrich; Stefan Bauer; Yash Sharma; Yoshua Bengio; Bernhard Schölkopf (9th International Conference on Learning Representations, ICLR 2021, Virtual Event, Austria, May 3-7, 2021, 2021)

Saliency is a Possible Red Herring When Diagnosing Poor Generalization - Joseph D. Viviano; Becks Simpson; Francis Dutil; Yoshua Bengio; Joseph Paul Cohen (9th International Conference on Learning Representations, ICLR 2021, Virtual Event, Austria, May 3-7, 2021, 2021)

Learning Neural Generative Dynamics for Molecular Conformation Generation - Minkai Xu; Shitong Luo; Yoshua Bengio; Jian Peng; Jian Tang (9th International Conference on Learning Representations, ICLR 2021, Virtual Event, Austria, May 3-7, 2021, 2021)

An End-to-End Framework for Molecular Conformation Generation via Bilevel Programming - Minkai Xu; Wujie Wang; Shitong Luo; Chence Shi; Yoshua Bengio; Rafael Gómez-Bombarelli; Jian Tang (Proceedings of the 38th International Conference on Machine Learning, ICML 2021, 18-24 July 2021, Virtual Event, 2021)

Combating False Negatives in Adversarial Imitation Learning - Konrad Zolna; Chitwan Saharia; Léonard Boussioux; David Yu-Tung Hui; Maxime Chevalier-Boisvert; Dzmitry Bahdanau; Yoshua Bengio (International Joint Conference on Neural Networks, IJCNN 2021, Shenzhen, China, July 18-22, 2021, 2021)

hBERT + BiasCorp - Fighting Racism on the Web - Olawale Onabola; Zhuang Ma; Yang Xie; Benjamin Akera; Abdulrahman Ibraheem; Jia Xue; Dianbo Liu; Yoshua Bengio (Proceedings of the First Workshop on Language Technology for Equality, Diversity and Inclusion, LT-EDI@EACL 2021, Online, April 19, 2021, 2021)

Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning - Nan Rosemary Ke; Aniket Didolkar; Sarthak Mittal; Anirudh Goyal; Guillaume Lajoie; Stefan Bauer; Danilo Jimenez Rezende; Michael Mozer; Yoshua Bengio; Chris Pal (Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, NeurIPS Datasets and Benchmarks 2021, December 2021, virtual, 2021)

Gradient Starvation: A Learning Proclivity in Neural Networks - Mohammad Pezeshki; Sékou-Oumar Kaba; Yoshua Bengio; Aaron C. Courville; Doina Precup; Guillaume Lajoie (Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual, 2021)

A Consciousness-Inspired Planning Agent for Model-Based Reinforcement Learning - Mingde Zhao; Zhen Liu; Sitao Luan; Shuyuan Zhang; Doina Precup; Yoshua Bengio (Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual, 2021)

Discrete-Valued Neural Communication - Dianbo Liu; Alex Lamb; Kenji Kawaguchi; Anirudh Goyal; Chen Sun; Michael C. Mozer; Yoshua Bengio (Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual, 2021)

Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization - Kartik Ahuja; Ethan Caballero; Dinghuai Zhang; Jean-Christophe Gagnon-Audet; Yoshua Bengio; Ioannis Mitliagkas; Irina Rish (Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual, 2021)

The Causal-Neural Connection: Expressiveness, Learnability, and Inference - Kevin Xia; Kai-Zhan Lee; Yoshua Bengio; Elias Bareinboim (Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual, 2021)

Dynamic Inference with Neural Interpreters - Nasim Rahaman; Muhammad Waleed Gondal; Shruti Joshi; Peter V. Gehler; Yoshua Bengio; Francesco Locatello; Bernhard Schölkopf (Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual, 2021)

Neural Production Systems - Aniket Didolkar; Anirudh Goyal; Nan Rosemary Ke; Charles Blundell; Philippe Beaudoin; Nicolas Heess; Michael Mozer; Yoshua Bengio (Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual, 2021)